Editor's note: The CEO Corner contains editors' compilations of business insights, which they have tailored for the dairy industry. The column inspires million-dollar dairy business owners to think like CEOs in other industries. Big data and predictive analytics for agriculture are here. Why now? Farmers are sick and tired of being left behind.

Cooley walt polo
Editor and Podcast Host / Progressive Dairy

“One of the worst feelings in the world is the shock of getting hit by a dropping market and being very exposed,” says Brandon Fish, CEO and founder of Indx.ag. “To have worked so hard to make a few bucks only to have it all wiped away by a turn in the market is a hard thing to deal with.”

Motivations similar to those of Fish, who wanted to figure out how to apply predictive analytics to protect his family’s hay business from economic downturns, is the reason you’ll likely see more big data applications in agriculture, and soon.

In a 2012 interview, McKinsey & Company director David Court predicted what would cause big data to take off:

“A few years ago the question was: ‘We have all this data. Surely there is something we can do with it?’ Now the question is: ‘I see my competitors exploiting this, and I feel like I’m getting behind.’ In fact, they are right. [The advantage it creates] is not a little bit of a difference; it’s a significant difference.”

Advertisement

Court predicted big data enters an industry when a company or individual members of an industry recognize they are falling behind. When big data and predictive analytics become a competitive advantage to others, then the rival industry will begin using big data technology in order to try to catch up, Court said.

That’s what Fish saw happening in agriculture.

“Predictive analytics have been used in financial markets since 1990,” Fish says. “Today, it’s estimated that it is used to do 70 percent of all trade in the markets. This technology is able to look at huge amounts of data and find correlations that would take you and me months to sort through. Instead of looking for correlations in the financial markets, we have applied this technology to the alfalfa hay market. We will soon be applying it to all the different agricultural markets as well.”

The 33-year-old Fish grew up bucking hay on a 3,000-acre hay farm in Poston, Arizona. His family has been in the alfalfa and bermudagrass hay marketing business for almost 40 years. Part of his motivation to learn predictive analytics was to protect hard-earned sweat equity – both his own family’s and that of others in agriculture.

“In 2008, we lost a lot of money because of the market dropping,” Fish says. “We had no idea it was coming. It happened again in 2014-2015, though not as severe. If we had known what was coming ahead of time, we could have reduced that loss.”

Fish commercially launched a new hay market report for California and western Arizona in August. It’s based on predictive computer analytics that he says can, on average, forecast changes in regional hay prices with 80 percent accuracy. In the coming months, Fish’s company will provide predictive analytics for publicly traded commodities, including corn, milk, wheat, soybeans, feeder cattle, coffee, sugar, cotton, live cattle, hogs, oat, rice, crude oil, natural gas, gold and silver.

“The computer is looking at huge amounts of data, then running different scenarios and correlations to find patterns within them. To date, we have run 3,000,000 different correlation scenarios. This would take a single person years to do, and we both know farmers, dairymen, brokers and exporters don’t have that kind of time,” Fish says.

While the computer is running all those scenarios, it is learning what data is important to pay attention to and other data that is not important, Fish explains. The end result of its calculations is a suggested outcome for short-term movements in hay prices.

“This technology can alert those in the industry to what is on the horizon, thus allowing them to prepare and plan,” Fish says. “I believe everyone could use an early warning system to let them know what’s coming. The more people we can get using this, the more affordable it will be for everyone.”

Fish’s new fee-based market report service is available to monthly ($17.88) or annual ($205.15) subscribers.

Fish says farmers shouldn’t completely ignore their “gut instinct” for prices, but rather add proven analytics into their decision-making process. Court said something similar:

“You need people that have a sense of the business and that are comfortable using the data and analytics. If you’re good at data analytics, but you don’t have a feel for the business, you’ll make naive decisions. If you’re comfortable with the feel of the business, but you never use analytics, you’re just leaving a lot of money on the table that your competitors are going to be able to exploit.”

Fish hopes his new predictive analytics will help those in agriculture catch up and “make more profit-generating decisions.”

“Agriculture is the least digitized industry in America today. Here is technology that can improve this vital industry and help the very people who provide so much for the rest of us. I believe it’s time that those working in the agricultural industry get an upgrade.”  end mark

Note: Our sister magazine, Progressive Forage, provides a monthly Hay Market Report as well. Subscribe here to get notifications when the latest news is available.

Walt Cooley

PHOTO: Illustration by staff.